French schwa and gradient cumulativity
Bibliographic Data
| ID | 22130705 |
|---|---|
| Authors | Brian Smith (0000-0002-6523-2019, University of Southern California), Brian W Smith (University of Southern California, Los Angeles, CA), Joe Pater (0000-0002-4784-3799, University of Massachusetts Amherst) |
| Year | 2020 |
| Volume | 5 |
| Issue | 1 |
| Publication date | 2020-03-05 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Glossa a journal of general linguistics (JOURNAL) |
| Journal identifiers | ISSN: 2397-1835 • E-ISSN: 2397-1835 |
| Publisher | Open Library of the Humanities (PUBLISHER) |
| DOI | 10.5334/gjgl.583 |
| OpenAlex | W2987146858 |
| Language | EN |
| Citations received | 12 |
| References cited | 25 |
We explore the interaction of two phonological factors that condition schwa–zero alternations in French: schwa is more likely after two consonants than a singleton; and schwa is more likely between stressed syllables than elsewhere. Using new data from a judgment study, we show that both factors play a role in schwa epenthesis and deletion, and that the two factors interact cumulatively: they have a stronger effect together than individually. Treating each factor as a constraint, we find that their cumulative interaction is better modeled with weighted than with ranked constraints. We provide a characterization of patterns of cumulativity in probability space in terms of the effect of constraint on its own versus its effect in a cumulative interaction with another constraint. Stochastic OT can model cumulative interactions, but only sublinear ones, where the effect of a constraint is weaker in the cumulative context than on its own. Weighted constraint models, MaxEnt and Noisy HG, can model the full range of cumulativity — sublinear, linear, and superlinear. In examining the ability of these models to fit our experimental data, we find that Stochastic OT is hampered by the fact that the data displays superlinear cumulativity. Noisy HG and MaxEnt fare better on this dataset, with MaxEnt yielding the best fit
Combinatorics · Geography · Schwa · Singleton · Speech recognition · Sublinear function · Computer Science · Linguistic Variation and Morphology · Mathematics · Natural Language Processing Techniques · Phonetics and Phonology Research
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| Unique citing works | 12 |
|---|---|
| Citations per year | 1,5 |
| Citation span | 2018 - 2024 (7) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 7 |